**4. Measurement and data requirements for network computation**

Any computation of a gas network is based on a model for the network structure and equipment accompanied by many data for the place and time of interest. These are data of materials, parameters of the medium, physical states, flow data (input and output) and controlling equipment. The sources of these data are shown schematically in table 2.

Fig. 5. Schematic data flow of reconstruction simulation for gas parameters/calorific value and feed back

consumers need gas with stable calorific value and/or Wobbe-Index. The allowed tolerance

By means of propane gas which has a higher calorific value (28.1 kWh/m3, approx.) the biogas will be mixed (conditioned) by special equipment to an appropriate final calorific value. The final value is selected and continuously controlled by the network operator depending on gas

The conditioning of gas is a high extra cost for the network operator (operational cost and propane, especially). An optimization of gas conditioning means that propane gas usage and cost should be minimized. This can be achieved in the conditioning equipment by selecting and setting the set point of the final calorific value to an acceptable low value. But this value must still be compatible with the calorific values in the surrounding network which - of course - must be known. Appropriate measurements, the mixing equations and

In gas network the gas flow may have a number feeder points – including different gas qualities - and in addition the intermeshed network structure contains potential mixing points at every pipe crossing or branch. Normally, insight of the gas flow and calorific value at certain interesting points in the intermeshed network is only possible by many measurements (e.g. gas chromatography) and/or network computation and simulation.

Any computation of a gas network is based on a model for the network structure and equipment accompanied by many data for the place and time of interest. These are data of materials, parameters of the medium, physical states, flow data (input and output) and

Fig. 5. Schematic data flow of reconstruction simulation for gas parameters/calorific value

controlling equipment. The sources of these data are shown schematically in table 2.

type (H or L), network structure, flow situation and consumer requirements.

simulation help to solve the optimization and set point problem, even on-line.

**4. Measurement and data requirements for network computation** 

in Germany/Europe is ± 2 %, only.

and feed back
